Evaluation of the STR typing kit PowerPlexk 16 with respect to technical performance and population genetics: a multicenter study

Size: px
Start display at page:

Download "Evaluation of the STR typing kit PowerPlexk 16 with respect to technical performance and population genetics: a multicenter study"

Transcription

1 International Congress Series 1239 (2003) Evaluation of the STR typing kit PowerPlexk 16 with respect to technical performance and population genetics: a multicenter study L. Henke a, *, A. Aaspollu b, R. Biondo c, B. Budowle d, K. Drobnic e, P.H. van Eede f, H. Felske-Zech g, L. Fernández de Simón h, L. Garafano i, C. Gehrig j, C. Luckenbach k, N. Malik l, M. Muche m, W. Parson n, D. Primorac o, P.M. Schneider p, J. Thomson q, D. Vanek r a Institut fuer Blutgruppenforschung, Cologne, Germany b National Institute of Chemical Physics and Biophysics, Laboratory of Molecular Genetics, Tallin 23, Estonia c Direzione Centrale della Polizia Criminale, Servizio Polizia Scientifica, Rome, Italy d FBI, Laboratory Division, Washington, DC, USA e Ministry of the Interior, 1000 Ljubljana, Slovenia f Sanquin, CLB Diagnostic Services, Immunogenetics, 1006 AD Amsterdam, Netherlands g Institut f. Rechtsmedizin, Freie Universitaet Berlin, Berlin, Germany h Instituto National de Toxicologia, Seccion de Biologia, Madrid, Spain i Raggruppamento Carabinieri Investigazoni Scientifiche, Sottocentro di Parma, Parma, Italy j Institut de Médecine Légale, 1211 Geneva 4, Switzerland k Institut für humangenetische Analytik, Tuebingen, Germany l Institut für Rechtsmedizin, Forensische Molekularbiologie, Universitaet Bern, 3012 Berne, Switzerland m Institut für Blutgruppenserologie und Genetik, Hamburg, Germany n Institut fuer Rechtsmedizin, Universitaet Innsbruck, 6020 Innsbruck, Austria o Laboratory for Clinical and Forensic Science, Clinical Hospital Split, Split, Croatia p Institut f. Rechtsmedizin, Universitaet Mainz, Mainz, Germany q LGC, Lifescience New Ventures Group, Teddington, Middlesex TW11 OLY, UK r Institute of Criminalistics Prague, Prague , Czech Republic Keywords: Forensic genetics; DNA; STR-polymorphisms; PowerPlex Introduction The recently distributed STR typing kit PowerPlexk 16 (Promega, Madison, USA) was evaluated in 17 different European laboratories. The kit amplifies the loci D3S1358, * Corresponding author. Tel.: ; fax: address: bgf.henke@t-online.de (L. Henke) /03 D 2003 Elsevier Science B.V. All rights reserved. PII: S (02)

2 790 L. Henke et al. / International Congress Series 1239 (2003) TH01, D21S11, D18S51, Penta E, D5S818, D13S317, D7S820, D16S539, CSF1PO, Penta D, Amelogenin, vwa, D8S1179, TPOX and FGA. This broad study focused on technical aspects including: the impact of the amount of target DNA, balance of loci, peak height differences in heterozygotes, comparison of genotyping results obtained with different primers as well as the analysis of population data and mutation rates. 2. Methods Each laboratory analysed unrelated individuals from its area with exception of the Teddington laboratory, which investigated individuals from immigration cases which could be assigned to either an Asian group (India, Pakistan and Bangladesh) or African Blacks. DNA was prepared from buccal swabs and blood by various well-established methods partially followed by quantification. PCR reaction volumes other than the recommended 25 Al varied from 10 to 50 Al. The analyses were performed on either an ABI 310 or ABI 377 analyses. Allele designation was performed by comparison with the allelic ladder provided with the kit. The allele frequencies were calculated from the number of each genotype of the sample set. Unbiased estimates of expected heterozygosity were computed as described by Edwards et al [1]. Possible deviation from Hardy Weinberg Equilibrium (HWE) was tested by calculating the unbiased estimate of the expected homozygote/heterozygote frequencies [2 4] and the exact test [5] based on 2000 shuffling experiments. The F ST values were determined as described by Weir and Cockerham [6]. 3. Results and discussion Each laboratory analysed persons which added up to a total number of 3698 individuals. Between 1876 (vwa) and 695 (D16S539), samples were tested with at least one different primer set (loci CSF1PO, D13S317, D16S539, D18S51, D21S11, D3S1358, D5S818, D7S820, D8S1179, FGA, TH01, TPOX and vwa). Results (19,555) were compared. At locus D8S1179, PowerPlexk 16 revealed heterozygotes in two parent/child pairs while amplification with AmpFlSTRR SGM Plus (Applied Biosystems, USA) showed only one allele. The parents were from either Vietnamese or Philippine decent. At locus TH01, one heterozygous sample (6/9.3) (PowerPlexk 16) showed only the allele 9.3 with AmpFlSTRR SGM Plus (ABI). At locus vwa, one person showed the phenotype 16/17 with PowerPlexk 16 while AmpFlSTRR SGM Plus and AmpFlSTRR Profiler 1 (ABI) amplified allele *16 only. Weak amplifications with PowerPlexk 16 were observed at loci FGA ( *24) and TPOX ( *9) in parent /child pairs while balanced peak heights were obtained with AmpFlSTRR Profiler 1 (ABI). At locus D5S818, weak amplifications of allele * 10 were observed with PowerPlexk 16 in two individuals. Locus CSF1PO showed a weak allele *8 with another sample while amplifications with Profiler 1 showed normal peaks. The balance of the amplicons was measured by comparing the mean peak heights from heterozygous loci. The inter loci balance for the blue systems is shown in Fig. 1. The

3 L. Henke et al. / International Congress Series 1239 (2003) Fig. 1. Interloci balance. Mean peak heights (RFU) of heterozygous loci D3 (n = 132), TH01 (n = 128), D21 (n = 134), D18 (n = 133) and Penta E (n = 131). peak height differences (%) in sister alleles of heterozygotes was calculated for the loci D3, TH01, D21, D18 and Penta E with allele 1 as the smaller allele. Most peak height differences were observed in the range from 10% to 30%: D3 (96.6%), TH01 (94.3%), D21 (95.9%), D18 (98.6%) and Penta E (83.5%) (Fig. 2). Peak height differences > 60% can be caused by either technical or genetic reasons. Control amplification with purified DNA can rule out technical reasons while transmission of the weaker allele gives a strong indication of incomplete primer matching in these loci. The allele frequencies of the various European populations were very similar while the Asian group and to a greater extent the group of African Blacks showed considerable differences. The genetic distance between the European populations varies between 0.96 Fig. 2. Peak height differences (%) of the sister alleles in heterozygotes. Allele 1 is the smaller allele.

4 792 Table 1 Allele frequenqies (%) at the locus Penta E, laboratory: Amsterdam (AMS), BERN, Hamburg (HAM), Innsbruck (INN), Koeln (KLN), Ljubljana (LJU), Madrid (MAD), Mainz (MZ), Parma (PAR), Prague (PRA), Rome (ROM), Split (SPL), Genève (SWI), Tallin (TAL), Tuebingen (TUE), Asian Group (TED_A), African Black (TED_B) Number of Alleles individuals tested AMS BERN HAM INN KLN LJU MAD MZ PAR PRA ROM SPL SWI TAL TUE TED_A TED_B L. Henke et al. / International Congress Series 1239 (2003)

5 Table 2 Allele frequenqies (%) at locus Penta D, laboratory: Amsterdam (AMS), BERN, Hamburg (HAM), Innsbruck (INN), Koeln (KLN), Ljubljana (LJU), Madrid (MAD), Mainz (MZ), Parma (PAR), Prague (PRA), Rome (ROM), Split (SPL), Genève (SWI), Tallin (TAL), Tuebingen (TUE), Asian Group (TED_A), African Black (TED_B) Number of Alleles individuals tested AMS BERN HAM INN KLN LJU MAD MZ PAR PRA ROM SPL SWI TAL TUE TED_A TED_B L. Henke et al. / International Congress Series 1239 (2003)

6 794 L. Henke et al. / International Congress Series 1239 (2003) Table 3 Meioses and genetic inconsistencies at loci Penta D and Penta E GEC Maternal meioses Paternal meioses Maternal inconsistencies Paternal inconsistencies Penta D (0.12%) Penta E (0.11%) 1 (0,12%) and Variants were observed at most loci. The frequencies for the loci Penta D and Penta E revealed a high level of polymorphism (Tables 1 and 2). In spite of the high general exclusion rates of Penta D and Penta E, their mutation rates were low (Table 3). All mutations observed at loci other than the Pentas were confirmed by using alternative primer sets. References [1] A. Edwards, H.A. Hammond, L. Jin, C.T. Caskey, R. Chakraborty, Genetic variation at five trimeric and tetrameric repeat loci in four human population groups, Genomics 12 (1992) [2] R. Chakraborty, P.E. Smouse, J.V. Neel, Population amalgation and genetic variation: observation and artificially agglomerated tribal populations of Central and South America, Am. J. Hum. Genet. 43 (1988) [3] M. Nei, Estimation of average heterozygosity and genetic distance from a small number of individuals, Genetics 89 (1978) [4] M. Nei, A.K. Roychoudhury, Sampling variances of heterozygosity and genetic distance, Genetics 76 (1974) [5] B. Budowle, B. Shea, S. Niezgoda, R. Chakraborty, CODIS STR loci data from 41 sample populations, J. Forensic Sci. 46 (3) (2001) [6] B.S. Weir, C.C. Cockerham, Estimating F-statistics for the analysis of population structure, Evolution 38 (1984)

Population genetic studies on the tetrameric short tandem repeat loci D3S1358, VWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317 and D7S820 in Egypt

Population genetic studies on the tetrameric short tandem repeat loci D3S1358, VWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317 and D7S820 in Egypt Forensic Science International 104 (1999) 31 www.elsevier.com/ locate/ forsciint Population genetic studies on the tetrameric short tandem repeat loci D3S1358, VWA, FGA, D8S1179, D21S11, D18S51, D5S818,

More information

Analysis of Y-STR Profiles in Mixed DNA using Next Generation Sequencing

Analysis of Y-STR Profiles in Mixed DNA using Next Generation Sequencing Analysis of Y-STR Profiles in Mixed DNA using Next Generation Sequencing So Yeun Kwon, Hwan Young Lee, and Kyoung-Jin Shin Department of Forensic Medicine, Yonsei University College of Medicine, Seoul,

More information

THE RARITY OF DNA PROFILES 1. BY BRUCE S. WEIR University of Washington

THE RARITY OF DNA PROFILES 1. BY BRUCE S. WEIR University of Washington The Annals of Applied Statistics 2007, Vol. 1, No. 2, 358 370 DOI: 10.1214/07-AOAS128 Institute of Mathematical Statistics, 2007 THE RARITY OF DNA PROFILES 1 BY BRUCE S. WEIR University of Washington It

More information

The statistical evaluation of DNA crime stains in R

The statistical evaluation of DNA crime stains in R The statistical evaluation of DNA crime stains in R Miriam Marušiaková Department of Statistics, Charles University, Prague Institute of Computer Science, CBI, Academy of Sciences of CR UseR! 2008, Dortmund

More information

arxiv: v1 [stat.ap] 7 Dec 2007

arxiv: v1 [stat.ap] 7 Dec 2007 The Annals of Applied Statistics 2007, Vol. 1, No. 2, 358 370 DOI: 10.1214/07-AOAS128 c Institute of Mathematical Statistics, 2007 THE RARITY OF DNA PROFILES 1 arxiv:0712.1099v1 [stat.ap] 7 Dec 2007 By

More information

Seminar: MPS applica/ons in the forensic DNA IDen/fica/on Solu/ons Vienna, May

Seminar: MPS applica/ons in the forensic DNA IDen/fica/on Solu/ons Vienna, May Seminar: MPS applica/ons in the forensic DNA workflow@human IDen/fica/on Solu/ons 2017 - Vienna, May 16 2017 Systematic Evaluation of the Early Access Applied Biosystems Precision ID Globalfiler Mixture

More information

Population Structure

Population Structure Ch 4: Population Subdivision Population Structure v most natural populations exist across a landscape (or seascape) that is more or less divided into areas of suitable habitat v to the extent that populations

More information

LECTURE # How does one test whether a population is in the HW equilibrium? (i) try the following example: Genotype Observed AA 50 Aa 0 aa 50

LECTURE # How does one test whether a population is in the HW equilibrium? (i) try the following example: Genotype Observed AA 50 Aa 0 aa 50 LECTURE #10 A. The Hardy-Weinberg Equilibrium 1. From the definitions of p and q, and of p 2, 2pq, and q 2, an equilibrium is indicated (p + q) 2 = p 2 + 2pq + q 2 : if p and q remain constant, and if

More information

Lecture 13: Variation Among Populations and Gene Flow. Oct 2, 2006

Lecture 13: Variation Among Populations and Gene Flow. Oct 2, 2006 Lecture 13: Variation Among Populations and Gene Flow Oct 2, 2006 Questions about exam? Last Time Variation within populations: genetic identity and spatial autocorrelation Today Variation among populations:

More information

1.5.1 ESTIMATION OF HAPLOTYPE FREQUENCIES:

1.5.1 ESTIMATION OF HAPLOTYPE FREQUENCIES: .5. ESTIMATION OF HAPLOTYPE FREQUENCIES: Chapter - 8 For SNPs, alleles A j,b j at locus j there are 4 haplotypes: A A, A B, B A and B B frequencies q,q,q 3,q 4. Assume HWE at haplotype level. Only the

More information

Characterization of Error Tradeoffs in Human Identity Comparisons: Determining a Complexity Threshold for DNA Mixture Interpretation

Characterization of Error Tradeoffs in Human Identity Comparisons: Determining a Complexity Threshold for DNA Mixture Interpretation Characterization of Error Tradeoffs in Human Identity Comparisons: Determining a Complexity Threshold for DNA Mixture Interpretation Boston University School of Medicine Program in Biomedical Forensic

More information

Forensic Genetics. Summer Institute in Statistical Genetics July 26-28, 2017 University of Washington. John Buckleton:

Forensic Genetics. Summer Institute in Statistical Genetics July 26-28, 2017 University of Washington. John Buckleton: Forensic Genetics Summer Institute in Statistical Genetics July 26-28, 2017 University of Washington John Buckleton: John.Buckleton@esr.cri.nz Bruce Weir: bsweir@uw.edu 1 Contents Topic Genetic Data, Evidence,

More information

Case-Control Association Testing. Case-Control Association Testing

Case-Control Association Testing. Case-Control Association Testing Introduction Association mapping is now routinely being used to identify loci that are involved with complex traits. Technological advances have made it feasible to perform case-control association studies

More information

Lecture 13: Population Structure. October 8, 2012

Lecture 13: Population Structure. October 8, 2012 Lecture 13: Population Structure October 8, 2012 Last Time Effective population size calculations Historical importance of drift: shifting balance or noise? Population structure Today Course feedback The

More information

Statistical Methods and Software for Forensic Genetics. Lecture I.1: Basics

Statistical Methods and Software for Forensic Genetics. Lecture I.1: Basics Statistical Methods and Software for Forensic Genetics. Lecture I.1: Basics Thore Egeland (1),(2) (1) Norwegian University of Life Sciences, (2) Oslo University Hospital Workshop. Monterrey, Mexico, Nov

More information

Workshop: Kinship analysis First lecture: Basics: Genetics, weight of evidence. I.1

Workshop: Kinship analysis First lecture: Basics: Genetics, weight of evidence. I.1 Workshop: Kinship analysis First lecture: Basics: Genetics, weight of evidence. I.1 Thore Egeland (1),(2), Klaas Slooten (3),(4) (1) Norwegian University of Life Sciences, (2) NIPH, (3) Netherlands Forensic

More information

Match probabilities in a finite, subdivided population

Match probabilities in a finite, subdivided population Match probabilities in a finite, subdivided population Anna-Sapfo Malaspinas a, Montgomery Slatkin a, Yun S. Song b, a Department of Integrative Biology, University of California, Berkeley, CA 94720, USA

More information

Neutral Theory of Molecular Evolution

Neutral Theory of Molecular Evolution Neutral Theory of Molecular Evolution Kimura Nature (968) 7:64-66 King and Jukes Science (969) 64:788-798 (Non-Darwinian Evolution) Neutral Theory of Molecular Evolution Describes the source of variation

More information

Stochastic Models for Low Level DNA Mixtures

Stochastic Models for Low Level DNA Mixtures Original Article en5 Stochastic Models for Low Level DNA Mixtures Dalibor Slovák 1,, Jana Zvárová 1, 1 EuroMISE Centre, Institute of Computer Science AS CR, Prague, Czech Republic Institute of Hygiene

More information

A paradigm shift in DNA interpretation John Buckleton

A paradigm shift in DNA interpretation John Buckleton A paradigm shift in DNA interpretation John Buckleton Specialist Science Solutions Manaaki Tangata Taiao Hoki protecting people and their environment through science I sincerely acknowledge conversations

More information

Processes of Evolution

Processes of Evolution 15 Processes of Evolution Forces of Evolution Concept 15.4 Selection Can Be Stabilizing, Directional, or Disruptive Natural selection can act on quantitative traits in three ways: Stabilizing selection

More information

Life Cycles, Meiosis and Genetic Variability24/02/2015 2:26 PM

Life Cycles, Meiosis and Genetic Variability24/02/2015 2:26 PM Life Cycles, Meiosis and Genetic Variability iclicker: 1. A chromosome just before mitosis contains two double stranded DNA molecules. 2. This replicated chromosome contains DNA from only one of your parents

More information

Drift Inflates Variance among Populations. Geographic Population Structure. Variance among groups increases across generations (Buri 1956)

Drift Inflates Variance among Populations. Geographic Population Structure. Variance among groups increases across generations (Buri 1956) Geographic Population Structure Alan R Rogers December 4, 205 / 26 Drift Inflates Variance among Populations 2 / 26 Variance among groups increases across generations Buri 956) 3 / 26 Gene flow migration)

More information

Statistical Genetics I: STAT/BIOST 550 Spring Quarter, 2014

Statistical Genetics I: STAT/BIOST 550 Spring Quarter, 2014 Overview - 1 Statistical Genetics I: STAT/BIOST 550 Spring Quarter, 2014 Elizabeth Thompson University of Washington Seattle, WA, USA MWF 8:30-9:20; THO 211 Web page: www.stat.washington.edu/ thompson/stat550/

More information

APPENDIX IV Data Tables

APPENDIX IV Data Tables APPENDIX IV Data Tables Table A1 National institutions supplying data 57 Table A2 Total population data, by country, 1999-2004 58 Table A3 Percentage age distribution of population, by country, 1999 2004

More information

Microevolution Changing Allele Frequencies

Microevolution Changing Allele Frequencies Microevolution Changing Allele Frequencies Evolution Evolution is defined as a change in the inherited characteristics of biological populations over successive generations. Microevolution involves the

More information

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics:

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics: Homework Assignment, Evolutionary Systems Biology, Spring 2009. Homework Part I: Phylogenetics: Introduction. The objective of this assignment is to understand the basics of phylogenetic relationships

More information

8. Genetic Diversity

8. Genetic Diversity 8. Genetic Diversity Many ways to measure the diversity of a population: For any measure of diversity, we expect an estimate to be: when only one kind of object is present; low when >1 kind of objects

More information

The EuCheMS Division Chemistry and the Environment EuCheMS/DCE

The EuCheMS Division Chemistry and the Environment EuCheMS/DCE The EuCheMS Division Chemistry and the Environment EuCheMS/DCE EuCheMS Division on Chemistry and the Environment was formed as a FECS Working Party in 1977. Membership: 37 members from 34 countries. Countries

More information

Levels of genetic variation for a single gene, multiple genes or an entire genome

Levels of genetic variation for a single gene, multiple genes or an entire genome From previous lectures: binomial and multinomial probabilities Hardy-Weinberg equilibrium and testing HW proportions (statistical tests) estimation of genotype & allele frequencies within population maximum

More information

EMEA Rents and Yields MarketView

EMEA Rents and Yields MarketView Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-00 Dec-01 Dec-02 Dec-03 Dec-04 Dec-05 Dec-06 Dec-07 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12 Dec-94 Dec-95 Dec-96 Dec-97 Dec-98 Dec-99 Dec-00 Dec-01 Dec-02 Dec-03

More information

Chem 4331 Name : Final Exam 2008

Chem 4331 Name : Final Exam 2008 Chem 4331 Name : Final Exam 2008 Answer any seven of questions 1-8. Each question is worth 15 points for a total of 105 points. 1. A crime has been committed, and a blood sample has been found at the crime

More information

Lecture 1: Case-Control Association Testing. Summer Institute in Statistical Genetics 2015

Lecture 1: Case-Control Association Testing. Summer Institute in Statistical Genetics 2015 Timothy Thornton and Michael Wu Summer Institute in Statistical Genetics 2015 1 / 1 Introduction Association mapping is now routinely being used to identify loci that are involved with complex traits.

More information

Overview of the Ibis SNP Assay

Overview of the Ibis SNP Assay Thomas Hall, Ph.D. Overview of the Ibis SNP ssay Objective PR/ESI MS based assay for human autosomal SNP analysis Exclude non contributors to a DN sample random profile match should have very low probability

More information

AEC 550 Conservation Genetics Lecture #2 Probability, Random mating, HW Expectations, & Genetic Diversity,

AEC 550 Conservation Genetics Lecture #2 Probability, Random mating, HW Expectations, & Genetic Diversity, AEC 550 Conservation Genetics Lecture #2 Probability, Random mating, HW Expectations, & Genetic Diversity, Today: Review Probability in Populatin Genetics Review basic statistics Population Definition

More information

Outline of lectures 3-6

Outline of lectures 3-6 GENOME 453 J. Felsenstein Evolutionary Genetics Autumn, 007 Population genetics Outline of lectures 3-6 1. We want to know what theory says about the reproduction of genotypes in a population. This results

More information

AALBORG UNIVERSITY. Investigation of a Gamma model for mixture STR samples

AALBORG UNIVERSITY. Investigation of a Gamma model for mixture STR samples AALBORG UNIVERSITY Investigation of a Gamma model for mixture STR samples by Susanne G. Bøttcher, E. Susanne Christensen, Steffen L. Lauritzen, Helle S. Mogensen and Niels Morling R-2006-32 Oktober 2006

More information

2. Map genetic distance between markers

2. Map genetic distance between markers Chapter 5. Linkage Analysis Linkage is an important tool for the mapping of genetic loci and a method for mapping disease loci. With the availability of numerous DNA markers throughout the human genome,

More information

Evolution of phenotypic traits

Evolution of phenotypic traits Quantitative genetics Evolution of phenotypic traits Very few phenotypic traits are controlled by one locus, as in our previous discussion of genetics and evolution Quantitative genetics considers characters

More information

Chromosome Chr Duplica Duplic t a ion Pixley

Chromosome Chr Duplica Duplic t a ion Pixley Chromosome Duplication Pixley Figure 4-6 Molecular Biology of the Cell ( Garland Science 2008) Figure 4-72 Molecular Biology of the Cell ( Garland Science 2008) Interphase During mitosis (cell division),

More information

UNIT 8 BIOLOGY: Meiosis and Heredity Page 148

UNIT 8 BIOLOGY: Meiosis and Heredity Page 148 UNIT 8 BIOLOGY: Meiosis and Heredity Page 148 CP: CHAPTER 6, Sections 1-6; CHAPTER 7, Sections 1-4; HN: CHAPTER 11, Section 1-5 Standard B-4: The student will demonstrate an understanding of the molecular

More information

Mechanisms of Evolution Microevolution. Key Concepts. Population Genetics

Mechanisms of Evolution Microevolution. Key Concepts. Population Genetics Mechanisms of Evolution Microevolution Population Genetics Key Concepts 23.1: Population genetics provides a foundation for studying evolution 23.2: Mutation and sexual recombination produce the variation

More information

Epigenetic vs. genetic diversity of stenoendemic short toothed sage (Salvia brachyodon Vandas)

Epigenetic vs. genetic diversity of stenoendemic short toothed sage (Salvia brachyodon Vandas) Epigenetic vs. genetic diversity of stenoendemic short toothed sage (Salvia brachyodon Vandas) Biruš, I., Liber, Z., Radosavljević, I., Bogdanović, S., Jug Dujaković, M., Zoldoš, V., Šatović, Z. Balkan

More information

EXERCISES FOR CHAPTER 3. Exercise 3.2. Why is the random mating theorem so important?

EXERCISES FOR CHAPTER 3. Exercise 3.2. Why is the random mating theorem so important? Statistical Genetics Agronomy 65 W. E. Nyquist March 004 EXERCISES FOR CHAPTER 3 Exercise 3.. a. Define random mating. b. Discuss what random mating as defined in (a) above means in a single infinite population

More information

D. Incorrect! That is what a phylogenetic tree intends to depict.

D. Incorrect! That is what a phylogenetic tree intends to depict. Genetics - Problem Drill 24: Evolutionary Genetics No. 1 of 10 1. A phylogenetic tree gives all of the following information except for. (A) DNA sequence homology among species. (B) Protein sequence similarity

More information

Chapter 13 Meiosis and Sexual Reproduction

Chapter 13 Meiosis and Sexual Reproduction Biology 110 Sec. 11 J. Greg Doheny Chapter 13 Meiosis and Sexual Reproduction Quiz Questions: 1. What word do you use to describe a chromosome or gene allele that we inherit from our Mother? From our Father?

More information

Question: If mating occurs at random in the population, what will the frequencies of A 1 and A 2 be in the next generation?

Question: If mating occurs at random in the population, what will the frequencies of A 1 and A 2 be in the next generation? October 12, 2009 Bioe 109 Fall 2009 Lecture 8 Microevolution 1 - selection The Hardy-Weinberg-Castle Equilibrium - consider a single locus with two alleles A 1 and A 2. - three genotypes are thus possible:

More information

BS 50 Genetics and Genomics Week of Oct 3 Additional Practice Problems for Section. A/a ; B/B ; d/d X A/a ; b/b ; D/d

BS 50 Genetics and Genomics Week of Oct 3 Additional Practice Problems for Section. A/a ; B/B ; d/d X A/a ; b/b ; D/d BS 50 Genetics and Genomics Week of Oct 3 Additional Practice Problems for Section 1. In the following cross, all genes are on separate chromosomes. A is dominant to a, B is dominant to b and D is dominant

More information

Problems for 3505 (2011)

Problems for 3505 (2011) Problems for 505 (2011) 1. In the simplex of genotype distributions x + y + z = 1, for two alleles, the Hardy- Weinberg distributions x = p 2, y = 2pq, z = q 2 (p + q = 1) are characterized by y 2 = 4xz.

More information

The Lander-Green Algorithm. Biostatistics 666 Lecture 22

The Lander-Green Algorithm. Biostatistics 666 Lecture 22 The Lander-Green Algorithm Biostatistics 666 Lecture Last Lecture Relationship Inferrence Likelihood of genotype data Adapt calculation to different relationships Siblings Half-Siblings Unrelated individuals

More information

Q Expected Coverage Achievement Merit Excellence. Punnett square completed with correct gametes and F2.

Q Expected Coverage Achievement Merit Excellence. Punnett square completed with correct gametes and F2. NCEA Level 2 Biology (91157) 2018 page 1 of 6 Assessment Schedule 2018 Biology: Demonstrate understanding of genetic variation and change (91157) Evidence Q Expected Coverage Achievement Merit Excellence

More information

Notes for MCTP Week 2, 2014

Notes for MCTP Week 2, 2014 Notes for MCTP Week 2, 2014 Lecture 1: Biological background Evolutionary biology and population genetics are highly interdisciplinary areas of research, with many contributions being made from mathematics,

More information

Outline of lectures 3-6

Outline of lectures 3-6 GENOME 453 J. Felsenstein Evolutionary Genetics Autumn, 009 Population genetics Outline of lectures 3-6 1. We want to know what theory says about the reproduction of genotypes in a population. This results

More information

Darwinian Selection. Chapter 7 Selection I 12/5/14. v evolution vs. natural selection? v evolution. v natural selection

Darwinian Selection. Chapter 7 Selection I 12/5/14. v evolution vs. natural selection? v evolution. v natural selection Chapter 7 Selection I Selection in Haploids Selection in Diploids Mutation-Selection Balance Darwinian Selection v evolution vs. natural selection? v evolution ² descent with modification ² change in allele

More information

Population genetics snippets for genepop

Population genetics snippets for genepop Population genetics snippets for genepop Peter Beerli August 0, 205 Contents 0.Basics 0.2Exact test 2 0.Fixation indices 4 0.4Isolation by Distance 5 0.5Further Reading 8 0.6References 8 0.7Disclaimer

More information

A maximum likelihood method to correct for allelic dropout in microsatellite data with no replicate genotypes

A maximum likelihood method to correct for allelic dropout in microsatellite data with no replicate genotypes Genetics: Published Articles Ahead of Print, published on July 30, 2012 as 10.1534/genetics.112.139519 A maximum likelihood method to correct for allelic dropout in microsatellite data with no replicate

More information

DNA polymorphisms such as SNP and familial effects (additive genetic, common environment) to

DNA polymorphisms such as SNP and familial effects (additive genetic, common environment) to 1 1 1 1 1 1 1 1 0 SUPPLEMENTARY MATERIALS, B. BIVARIATE PEDIGREE-BASED ASSOCIATION ANALYSIS Introduction We propose here a statistical method of bivariate genetic analysis, designed to evaluate contribution

More information

Chapter 16. Table of Contents. Section 1 Genetic Equilibrium. Section 2 Disruption of Genetic Equilibrium. Section 3 Formation of Species

Chapter 16. Table of Contents. Section 1 Genetic Equilibrium. Section 2 Disruption of Genetic Equilibrium. Section 3 Formation of Species Population Genetics and Speciation Table of Contents Section 1 Genetic Equilibrium Section 2 Disruption of Genetic Equilibrium Section 3 Formation of Species Section 1 Genetic Equilibrium Objectives Identify

More information

Population Genetic Data Analysis (revised July 13, 2018)

Population Genetic Data Analysis (revised July 13, 2018) Population Genetic Data Analysis (revised July 13, 2018) Summer Institute in Statistical Genetics University of Washington July 11-13, 2018 Jérôme Goudet: jerome.goudet@unil.ch Bruce Weir: bsweir@uw.edu

More information

Supporting Online Material for

Supporting Online Material for www.sciencemag.org/cgi/content/full/331/6019/876/dc1 Supporting Online Material for Synthetic Clonal Reproduction Through Seeds Mohan P. A. Marimuthu, Sylvie Jolivet, Maruthachalam Ravi, Lucie Pereira,

More information

Outline. P o purple % x white & white % x purple& F 1 all purple all purple. F purple, 224 white 781 purple, 263 white

Outline. P o purple % x white & white % x purple& F 1 all purple all purple. F purple, 224 white 781 purple, 263 white Outline - segregation of alleles in single trait crosses - independent assortment of alleles - using probability to predict outcomes - statistical analysis of hypotheses - conditional probability in multi-generation

More information

Gene mapping, linkage analysis and computational challenges. Konstantin Strauch

Gene mapping, linkage analysis and computational challenges. Konstantin Strauch Gene mapping, linkage analysis an computational challenges Konstantin Strauch Institute for Meical Biometry, Informatics, an Epiemiology (IMBIE) University of Bonn E-mail: strauch@uni-bonn.e Genetics an

More information

Breeding Values and Inbreeding. Breeding Values and Inbreeding

Breeding Values and Inbreeding. Breeding Values and Inbreeding Breeding Values and Inbreeding Genotypic Values For the bi-allelic single locus case, we previously defined the mean genotypic (or equivalently the mean phenotypic values) to be a if genotype is A 2 A

More information

Conservation Genetics. Outline

Conservation Genetics. Outline Conservation Genetics The basis for an evolutionary conservation Outline Introduction to conservation genetics Genetic diversity and measurement Genetic consequences of small population size and extinction.

More information

Application Evolution: Part 1.1 Basics of Coevolution Dynamics

Application Evolution: Part 1.1 Basics of Coevolution Dynamics Application Evolution: Part 1.1 Basics of Coevolution Dynamics S. chilense S. peruvianum Summer Semester 2013 Prof Aurélien Tellier FG Populationsgenetik Color code Color code: Red = Important result or

More information

Evolution of Populations. Chapter 17

Evolution of Populations. Chapter 17 Evolution of Populations Chapter 17 17.1 Genes and Variation i. Introduction: Remember from previous units. Genes- Units of Heredity Variation- Genetic differences among individuals in a population. New

More information

Population Genetics & Evolution

Population Genetics & Evolution The Theory of Evolution Mechanisms of Evolution Notes Pt. 4 Population Genetics & Evolution IMPORTANT TO REMEMBER: Populations, not individuals, evolve. Population = a group of individuals of the same

More information

Yesterday s Picture UNIT 3D

Yesterday s Picture UNIT 3D Warm-Up Blood types are determined by a single gene with several alleles. The allele encoding the Type A phenotype (I A ) is dominant to the allele encoding the Type O phenotype (i). Determine the phenotype

More information

GeneMapper ID-X Software Version 1.1 (Mixture Analysis Tool)

GeneMapper ID-X Software Version 1.1 (Mixture Analysis Tool) Getting Started Guide GeneMapper ID-X Software Version 1.1 (Mixture Analysis Tool) Note: To improve the clarity of graphics in this PDF file, use the zoom tool to increase magnification to 150% or greater.

More information

19. Genetic Drift. The biological context. There are four basic consequences of genetic drift:

19. Genetic Drift. The biological context. There are four basic consequences of genetic drift: 9. Genetic Drift Genetic drift is the alteration of gene frequencies due to sampling variation from one generation to the next. It operates to some degree in all finite populations, but can be significant

More information

Applications Note 224 April 2010

Applications Note 224 April 2010 Applications Note 224 April 21 Validation of the Eppendorf epmotion 575 TMX System for use with the Applied Biosystems Prepfiler Automated Forensic DNA Extraction Kit Nicole Bolin, Melissa Beddow, MSFS,

More information

For 5% confidence χ 2 with 1 degree of freedom should exceed 3.841, so there is clear evidence for disequilibrium between S and M.

For 5% confidence χ 2 with 1 degree of freedom should exceed 3.841, so there is clear evidence for disequilibrium between S and M. STAT 550 Howework 6 Anton Amirov 1. This question relates to the same study you saw in Homework-4, by Dr. Arno Motulsky and coworkers, and published in Thompson et al. (1988; Am.J.Hum.Genet, 42, 113-124).

More information

Rules of decision that are not tailored to individual cases, such as those that turn on statistical reasoning, are often viewed as suspect.

Rules of decision that are not tailored to individual cases, such as those that turn on statistical reasoning, are often viewed as suspect. Section 1: Overview HISTORY OF IDENTIFICATION Legal v. Scientific Thinking The very goals of science and law differ. Science searches for the truth and seeks to increase knowledge by formulating and testing

More information

Quantitative characters II: heritability

Quantitative characters II: heritability Quantitative characters II: heritability The variance of a trait (x) is the average squared deviation of x from its mean: V P = (1/n)Σ(x-m x ) 2 This total phenotypic variance can be partitioned into components:

More information

KIR gene polymorphism study in the Uygur population in Xinjiang, China

KIR gene polymorphism study in the Uygur population in Xinjiang, China KIR gene polymorphism study in the Uygur population in Xinjiang, China G.-Y. Lin and Y.-B. Wang No. 474 Hospital of Chinese PLA, Urumqi, China Corresponding author: G.-Y. Lin E-mail: lgy474@yeah.net Genet.

More information

Classical Selection, Balancing Selection, and Neutral Mutations

Classical Selection, Balancing Selection, and Neutral Mutations Classical Selection, Balancing Selection, and Neutral Mutations Classical Selection Perspective of the Fate of Mutations All mutations are EITHER beneficial or deleterious o Beneficial mutations are selected

More information

Lecture WS Evolutionary Genetics Part I 1

Lecture WS Evolutionary Genetics Part I 1 Quantitative genetics Quantitative genetics is the study of the inheritance of quantitative/continuous phenotypic traits, like human height and body size, grain colour in winter wheat or beak depth in

More information

Outline for today s lecture (Ch. 14, Part I)

Outline for today s lecture (Ch. 14, Part I) Outline for today s lecture (Ch. 14, Part I) Ploidy vs. DNA content The basis of heredity ca. 1850s Mendel s Experiments and Theory Law of Segregation Law of Independent Assortment Introduction to Probability

More information

Segregation versus mitotic recombination APPENDIX

Segregation versus mitotic recombination APPENDIX APPENDIX Waiting time until the first successful mutation The first time lag, T 1, is the waiting time until the first successful mutant appears, creating an Aa individual within a population composed

More information

Linear Regression (1/1/17)

Linear Regression (1/1/17) STA613/CBB540: Statistical methods in computational biology Linear Regression (1/1/17) Lecturer: Barbara Engelhardt Scribe: Ethan Hada 1. Linear regression 1.1. Linear regression basics. Linear regression

More information

Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin

Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin Solutions to Even-Numbered Exercises to accompany An Introduction to Population Genetics: Theory and Applications Rasmus Nielsen Montgomery Slatkin CHAPTER 1 1.2 The expected homozygosity, given allele

More information

EVOLUTION UNIT. 3. Unlike his predecessors, Darwin proposed a mechanism by which evolution could occur called.

EVOLUTION UNIT. 3. Unlike his predecessors, Darwin proposed a mechanism by which evolution could occur called. EVOLUTION UNIT Name Read Chapters 1.3, 20, 21, 22, 24.1 and 35.9 and complete the following. Chapter 1.3 Review from The Science of Biology 1. Discuss the influences, experiences and observations that

More information

Hinda Haned. May 25, Introduction 3. 2 Getting started forensim installation How to get help... 3

Hinda Haned. May 25, Introduction 3. 2 Getting started forensim installation How to get help... 3 A tutorial for the package forensim Hinda Haned May 5, 013 Contents 1 Introduction 3 Getting started 3.1 forensim installation........................... 3. How to get help.............................

More information

The Wright-Fisher Model and Genetic Drift

The Wright-Fisher Model and Genetic Drift The Wright-Fisher Model and Genetic Drift January 22, 2015 1 1 Hardy-Weinberg Equilibrium Our goal is to understand the dynamics of allele and genotype frequencies in an infinite, randomlymating population

More information

MARKER ASSISTED SELECTION (MAS) FOR DROUGHT TOLERANCE IN WHEAT USING MARKERS ASSOCIATED WITH MEMBRANE STABILITY

MARKER ASSISTED SELECTION (MAS) FOR DROUGHT TOLERANCE IN WHEAT USING MARKERS ASSOCIATED WITH MEMBRANE STABILITY AN. I.N.C.D.A. FUNDULEA, VOL. LXXVII, 2009 GENETICA ŞI AMELIORAREA PLANTELOR MARKER ASSISTED SELECTION (MAS) FOR DROUGHT TOLERANCE IN WHEAT USING MARKERS ASSOCIATED WITH MEMBRANE STABILITY SELECŢIA ASISTATĂ

More information

genome a specific characteristic that varies from one individual to another gene the passing of traits from one generation to the next

genome a specific characteristic that varies from one individual to another gene the passing of traits from one generation to the next genetics the study of heredity heredity sequence of DNA that codes for a protein and thus determines a trait genome a specific characteristic that varies from one individual to another gene trait the passing

More information

DNA Structure and Function

DNA Structure and Function DNA Structure and Function Nucleotide Structure 1. 5-C sugar RNA ribose DNA deoxyribose 2. Nitrogenous Base N attaches to 1 C of sugar Double or single ring Four Bases Adenine, Guanine, Thymine, Cytosine

More information

Genetics and Natural Selection

Genetics and Natural Selection Genetics and Natural Selection Darwin did not have an understanding of the mechanisms of inheritance and thus did not understand how natural selection would alter the patterns of inheritance in a population.

More information

Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate.

Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate. OEB 242 Exam Practice Problems Answer Key Q1) Explain how background selection and genetic hitchhiking could explain the positive correlation between genetic diversity and recombination rate. First, recall

More information

Calculation of IBD probabilities

Calculation of IBD probabilities Calculation of IBD probabilities David Evans and Stacey Cherny University of Oxford Wellcome Trust Centre for Human Genetics This Session IBD vs IBS Why is IBD important? Calculating IBD probabilities

More information

GBLUP and G matrices 1

GBLUP and G matrices 1 GBLUP and G matrices 1 GBLUP from SNP-BLUP We have defined breeding values as sum of SNP effects:! = #$ To refer breeding values to an average value of 0, we adopt the centered coding for genotypes described

More information

WHO EpiData. A monthly summary of the epidemiological data on selected Vaccine preventable diseases in the WHO European Region

WHO EpiData. A monthly summary of the epidemiological data on selected Vaccine preventable diseases in the WHO European Region A monthly summary of the epidemiological data on selected Vaccine preventable diseases in the WHO European Region Table 1: Reported cases for the period January December 2018 (data as of 01 February 2019)

More information

Online Appendix for Cultural Biases in Economic Exchange? Luigi Guiso Paola Sapienza Luigi Zingales

Online Appendix for Cultural Biases in Economic Exchange? Luigi Guiso Paola Sapienza Luigi Zingales Online Appendix for Cultural Biases in Economic Exchange? Luigi Guiso Paola Sapienza Luigi Zingales 1 Table A.1 The Eurobarometer Surveys The Eurobarometer surveys are the products of a unique program

More information

Introduction to Advanced Population Genetics

Introduction to Advanced Population Genetics Introduction to Advanced Population Genetics Learning Objectives Describe the basic model of human evolutionary history Describe the key evolutionary forces How demography can influence the site frequency

More information

Multimedia on Nuclear Reactor Physics In order to improve education and training quality, a Multimedia on Nuclear Reactor Physics has been developed.

Multimedia on Nuclear Reactor Physics In order to improve education and training quality, a Multimedia on Nuclear Reactor Physics has been developed. MULTIMEDIA ON NUCLEAR REACTOR PHYSICS Prof. PhD. Javier Dies, Doctor Engineer Professor Chair in Nuclear Engineering g Upc- Barcelona-Tech, Spain Nuclear Engineering Research Group (NERG), Departament

More information

A gamma model for DNA mixture analyses

A gamma model for DNA mixture analyses Bayesian Analysis (2007) 2, Number 2, pp. 333 348 A gamma model for DNA mixture analyses R. G. Cowell, S. L. Lauritzen and J. Mortera Abstract. We present a new methodology for analysing forensic identification

More information

BIG IDEA 4: BIOLOGICAL SYSTEMS INTERACT, AND THESE SYSTEMS AND THEIR INTERACTIONS POSSESS COMPLEX PROPERTIES.

BIG IDEA 4: BIOLOGICAL SYSTEMS INTERACT, AND THESE SYSTEMS AND THEIR INTERACTIONS POSSESS COMPLEX PROPERTIES. Enduring Understanding 4.C Independent Study Assignment Assignment Instructions Both components of this assignment (Part I and Part II) should be completed on the pages provided. Each numbered component

More information

Multiple paternity and hybridization in two smooth-hound sharks

Multiple paternity and hybridization in two smooth-hound sharks Multiple paternity and hybridization in two smooth-hound sharks Ilaria A. M. Marino 1, Emilio Riginella 1, Michele Gristina 2, Maria B. Rasotto 1, Lorenzo Zane 1*, Carlotta Mazzoldi 1 1 Department of Biology,

More information

Big Idea #1: The process of evolution drives the diversity and unity of life

Big Idea #1: The process of evolution drives the diversity and unity of life BIG IDEA! Big Idea #1: The process of evolution drives the diversity and unity of life Key Terms for this section: emigration phenotype adaptation evolution phylogenetic tree adaptive radiation fertility

More information

MODULE NO.22: Probability

MODULE NO.22: Probability SUBJECT Paper No. and Title Module No. and Title Module Tag PAPER No.13: DNA Forensics MODULE No.22: Probability FSC_P13_M22 TABLE OF CONTENTS 1. Learning Outcomes 2. Introduction 3. Laws of Probability

More information